MétaCan
Menu
Back to cohort
Record W4409325046 · doi:10.1063/4.0000447

Minor Homemade Tools For Use With PXRD

2025· article· en· W4409325046 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStructural Dynamics · 2025
Typearticle
Languageen
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
Fundersnot available
KeywordsPowder diffractionMinor (academic)Computer scienceInformation retrievalChemistryCrystallography

Abstract

fetched live from OpenAlex

There are many standard tools used in PXRD data acquisition: a razor or glass slide for levelling off a sample, a zero background diffraction plate, and so on. However, sometimes you need a tool that isn't commercially available, even if it's well documented in the literature, such as a straight-walled scoop for the Linear Japan Cake Method or a taller blade to fit over the short one installed on Bruker's air-sensitive zero-background diffraction plate. The creation and use of these tools will be outlined, along with instructions for making a most useful invention: a heavy block of metal with one side roughed and one side smooth. Additionally, the uses of the PXRDreport.py software tool will be outlined.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.099
GPT teacher head0.377
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it